Optimal energy management for a flywheel-assisted battery electric vehicle

被引:12
|
作者
Dhand, Aditya [1 ]
Pullen, Keith [1 ]
机构
[1] City Univ London, Sch Engn & Math Sci, London EC1V 0HB, England
关键词
Flywheel; battery electric vehicle; energy management; dynamic programming; hybrid vehicle; SUPERVISORY CONTROL; STORAGE SYSTEMS; HYBRID; STRATEGIES;
D O I
10.1177/0954407014567720
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Battery electric vehicles are crucial to the reduction in the dependence on fossil fuels and for moving towards a zero-emission transport system. Although battery electric vehicle technology has been rapidly improving, the limited driving range and the high cost are significant impediments to the popularity of electric vehicles. The battery is the main element which affects the range and the cost of the vehicle. The batteries can provide either high power or high energy but not both. Hybridisation of the energy source is one of the methods to improve the energy efficiency of the vehicle, which involves combining a high-energy battery with a high-power source. High-speed flywheels have attractive properties and low-cost potential which makes them excellent secondary energy storage devices to be used in hybrid and electric vehicles. They are utilised to load the battery to a level so as to protect it from peak loads and to enhance its capacity and life. The flywheel is coupled to the drive line with a continuously variable transmission. This paper presents the optimal energy management strategy for a mechanically connected flywheel-assisted battery electric vehicle powertrain. The optimisation problem is complex because of factors such as the small storage capacity of the flywheel, the kinematic constraints and the slipping of clutches. Dynamic programming is used to calculate the optimal control strategy for torque distribution during operation in real-world driving cycles. The results show significant potential for reduction in the energy consumption in extra-urban and highway cycles, while reducing the peak battery loads during all cycles. The results give a benchmark of the energy-saving potential for such a powertrain and insights into how a real suboptimal controller can be designed.
引用
收藏
页码:1672 / 1682
页数:11
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